Sur la Restauration et l'Edition de Vidéo : Détection de Rayures et Inpainting de Scènes Complexes

The inevitable degradation of visual content such as images and films leads to the goal ofimage and video restoration. In this thesis, we look at two specific restoration problems : the detection ofline scratches in old films and the automatic completion of videos, or video inpainting as it is also known.Line scratches are caused when the film physically rubs against a mechanical part. This origin resultsin the specific characteristics of the defect, such as verticality and temporal persistence. We propose adetection algorithm based on the statistical approach known as a contrario methods. We also proposea temporal filtering step to remove false alarms present in the first detection step. Comparisons withprevious work show improved recall and precision, and robustness with respect to the presence of noiseand clutter in the film.The second part of the thesis concerns video inpainting. We propose an algorithm based on theminimisation of a patch-based functional of the video content. In this framework, we address the followingproblems : extremely high execution times, the correct handling of textures in the video and inpaintingwith moving cameras. We also address some convergence issues in a very simplified inpainting context.La degradation inévitable des contenus visuels (images, films) conduit nécessairementà la tâche de la restauration des images et des vidéos. Dans cetre thèse, nous nous intéresserons àdeux sous-problèmes de restauration : la détection des rayures dans les vieux films, et le remplissageautomatique des vidéos (“inpainting vidéo en anglais).En général, les rayures sont dues aux frottements de la pellicule du film avec un objet lors de laprojection du film. Les origines physiques de ce défaut lui donnent des caractéristiques très particuliers.Les rayures sont des lignes plus ou moins verticales qui peuvent être blanches ou noires (ou parfois encouleur) et qui sont temporellement persistantes, c’est-à-dire qu’elles ont une position qui est continuedans le temps. Afin de détecter ces défauts, nous proposons d’abord un algorithme de détection basésur un ensemble d’approches statistiques appelées les méthodes a contrario. Cet algorithme fournitune détection précise et robuste aux bruits et aux textures présentes dans l’image. Nous proposonségalement une étape de filtrage temporel afin d’écarter les fausses alarmes de la première étape dedétection. Celle-ci améliore la précision de l’algorithme en analysant le mouvement des détections spatiales.L’ensemble de l’algorithme (détection spatiale et filtrage temporel) est comparé à des approchesde la littérature et montre un rappel et une précision grandement améliorés.La deuxième partie de cette thèse est consacrée à l’inpainting vidéo. Le but ici est de remplirune région d’une vidéo avec un contenu qui semble visuellement cohérent et convaincant. Il existeune pléthore de méthodes qui traite ce problème dans le cas des images. La littérature dans le casdes vidéos est plus restreinte, notamment car le temps d’exécution représente un véritable obstacle.Nous proposons un algorithme d’inpainting vidéo qui vise l’optimisation d’une fonctionnelle d’énergiequi intègre la notion de patchs, c’est-à-dire des petits cubes de contenu vidéo. Nous traitons d’abord leprobl’‘eme du temps d’exécution avant d’attaquer celui de l’inpainting satisfaisant des textures dans lesvidéos. Nous traitons également le cas des vidéos dont le fond est en mouvement ou qui ont été prisesavec des caméras en mouvement. Enfin, nous nous intéressons à certaines questions de convergencede l’algorithme dans des cas très simplifiés

Multisensory Imagery Cues for Object Separation, Specularity Detection and Deep Learning based Inpainting

Multisensory imagery cues have been actively investigated in diverse applications in the computer vision community to provide additional geometric information that is either absent or difficult to capture from mainstream two-dimensional imaging. The inherent features of multispectral polarimetric light field imagery (MSPLFI) include object distribution over spectra, surface properties, shape, shading and pixel flow in light space. The aim of this dissertation is to explore these inherent properties to exploit new structures and methodologies for the tasks of object separation, specularity detection and deep learning-based inpainting in MSPLFI. In the first part of this research, an application to separate foreground objects from the background in both outdoor and indoor scenes using multispectral polarimetric imagery (MSPI) cues is examined. Based on the pixel neighbourhood relationship, an on-demand clustering technique is proposed and implemented to separate artificial objects from natural background in a complex outdoor scene. However, due to indoor scenes only containing artificial objects, with vast variations in energy levels among spectra, a multiband fusion technique followed by a background segmentation algorithm is proposed to separate the foreground from the background. In this regard, first, each spectrum is decomposed into low and high frequencies using the fast Fourier transform (FFT) method. Second, principal component analysis (PCA) is applied on both frequency images of the individual spectrum and then combined with the first principal components as a fused image. Finally, a polarimetric background segmentation (BS) algorithm based on the Stokes vector is proposed and implemented on the fused image. The performance of the proposed approaches are evaluated and compared using publicly available MSPI datasets and the dice similarity coefficient (DSC). The proposed multiband fusion and BS methods demonstrate better fusion quality and higher segmentation accuracy compared with other studies for several metrics, including mean absolute percentage error (MAPE), peak signal-to-noise ratio (PSNR), Pearson correlation coefficient (PCOR) mutual information (MI), accuracy, Geometric Mean (G-mean), precision, recall and F1-score. In the second part of this work, a twofold framework for specular reflection detection (SRD) and specular reflection inpainting (SRI) in transparent objects is proposed. The SRD algorithm is based on the mean, the covariance and the Mahalanobis distance for predicting anomalous pixels in MSPLFI. The SRI algorithm first selects four-connected neighbouring pixels from sub-aperture images and then replaces the SRD pixel with the closest matched pixel. For both algorithms, a 6D MSPLFI transparent object dataset is captured from multisensory imagery cues due to the unavailability of this kind of dataset. The experimental results demonstrate that the proposed algorithms predict higher SRD accuracy and better SRI quality than the existing approaches reported in this part in terms of F1-score, G-mean, accuracy, the structural similarity index (SSIM), the PSNR, the mean squared error (IMMSE) and the mean absolute deviation (MAD). However, due to synthesising SRD pixels based on the pixel neighbourhood relationship, the proposed inpainting method in this research produces artefacts and errors when inpainting large specularity areas with irregular holes. Therefore, in the last part of this research, the emphasis is on inpainting large specularity areas with irregular holes based on the deep feature extraction from multisensory imagery cues. The proposed six-stage deep learning inpainting (DLI) framework is based on the generative adversarial network (GAN) architecture and consists of a generator network and a discriminator network. First, pixels’ global flow in the sub-aperture images is calculated by applying the large displacement optical flow (LDOF) method. The proposed training algorithm combines global flow with local flow and coarse inpainting results predicted from the baseline method. The generator attempts to generate best-matched features, while the discriminator seeks to predict the maximum difference between the predicted results and the actual results. The experimental results demonstrate that in terms of the PSNR, MSSIM, IMMSE and MAD, the proposed DLI framework predicts superior inpainting quality to the baseline method and the previous part of this research

Characterising pattern asymmetry in pigmented skin lesions

Abstract. In clinical diagnosis of pigmented skin lesions asymmetric pigmentation is often indicative of melanoma. This paper describes a method and measures for characterizing lesion symmetry. The estimate of mirror symmetry is computed first for a number of axes at different degrees of rotation with respect to the lesion centre. The statistics of these estimates are the used to assess the overall symmetry. The method is applied to three different lesion representations showing the overall pigmentation, the pigmentation pattern, and the pattern of dermal melanin. The best measure is a 100% sensitive and 96% specific indicator of melanoma on a test set of 33 lesions, with a separate training set consisting of 66 lesions

A hybrid piezoelectric and electrostatic energy harvester for scavenging arterial pulsations

Implantable and wearable biomedical devices suffer from a limited lifespan of on-board batteries which results in a requirement to change the battery or the device itself causing additional physical discomfort. In order to overcome this, various energy harvesters have been developed. The human body possesses several types of energy available for scavenging through appropriately designed energy harvesting devices, while cardiovascular system in particular represents a constant reliable source of mechanical energy from vibration. Most conventional energy harvesters exploit only a single phenomenon, such piezo- or triboelectricity, thus producing reduced power density. As an improvement, hybridisation of energy harvesters intends to negate this drawback by simultaneously scavenging energy by multiple harvesters. In the present work, the reverse electrowetting on dielectric (REWOD) phenomenon is combined with the piezoelectric effect in a proof-of-concept hybrid harvester for scavenging biomechanical energy from arterial or other type pulsations. A mathematical model of the harvester was developed, and a computational investigation using CFD, and fluid-structure interaction simulations were carried out using the COMSOL Multiphysics software. The effect of the materials of piezoelectric film and geometrical features of the harvester on parameters such as the displacement, the frequency of pulsations and the energy produced were studied. An experimental setup that could imitate the displacements caused from arterial pulsations was designed and the produced electrical energy characteristics were analysed. A comparison between experimental and computational data was carried out and demonstrated a good agreement. Dependencies between geometrical parameters and electrical output were obtained, recommendation on piezoelectric materials and design solutions were provided

Land Use Conflict Detection and Multi-Objective Optimization Based on the Productivity, Sustainability, and Livability Perspective

Land use affects many aspects of regional sustainable development, so insight into its influence is of great importance for the optimization of national space. The book mainly focuses on functional classification, spatial conflict detection, and spatial development pattern optimization based on productivity, sustainability, and livability perspectives, presenting a relevant opportunity for all scholars to share their knowledge from the multidisciplinary community across the world that includes landscape ecologists, social scientists, and geographers. The book is systematically organized into the optimization theory, methods, and practices for PLES (production–living–ecological space) around territorial spatial planning, with the overall planning of PLES as the goal and the promotion of ecological civilization construction as the starting point. Through this, the competition and synergistic interactions and positive feedback mechanisms between population, resources, ecology, environment, and economic and social development in the PLES system were revealed, and the nonlinear dynamic effects among subsystems and elements in the system identified. In addition, a series of optimization approaches for PLES is proposed

Across Space and Time. Papers from the 41st Conference on Computer Applications and Quantitative Methods in Archaeology, Perth, 25-28 March 2013

This volume presents a selection of the best papers presented at the forty-first annual Conference on Computer Applications and Quantitative Methods in Archaeology. The theme for the conference was "Across Space and Time", and the papers explore a multitude of topics related to that concept, including databases, the semantic Web, geographical information systems, data collection and management, and more